Auswahl der wissenschaftlichen Literatur zum Thema „Subspaces methods“
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Zeitschriftenartikel zum Thema "Subspaces methods"
Eiermann, Michael, und Oliver G. Ernst. „Geometric aspects of the theory of Krylov subspace methods“. Acta Numerica 10 (Mai 2001): 251–312. http://dx.doi.org/10.1017/s0962492901000046.
Der volle Inhalt der QuelleFreund, Roland W. „Model reduction methods based on Krylov subspaces“. Acta Numerica 12 (Mai 2003): 267–319. http://dx.doi.org/10.1017/s0962492902000120.
Der volle Inhalt der QuelleSia, Florence, und Rayner Alfred. „Tree-based mining contrast subspace“. International Journal of Advances in Intelligent Informatics 5, Nr. 2 (23.07.2019): 169. http://dx.doi.org/10.26555/ijain.v5i2.359.
Der volle Inhalt der QuelleLENG, JINSONG, und ZHIHU HUANG. „OUTLIERS DETECTION WITH CORRELATED SUBSPACES FOR HIGH DIMENSIONAL DATASETS“. International Journal of Wavelets, Multiresolution and Information Processing 09, Nr. 02 (März 2011): 227–36. http://dx.doi.org/10.1142/s0219691311004067.
Der volle Inhalt der QuelleLaaksonen, Jorma, und Erkki Oja. „Learning Subspace Classifiers and Error-Corrective Feature Extraction“. International Journal of Pattern Recognition and Artificial Intelligence 12, Nr. 04 (Juni 1998): 423–36. http://dx.doi.org/10.1142/s0218001498000270.
Der volle Inhalt der QuelleSeshadri, P., S. Yuchi, G. T. Parks und S. Shahpar. „Supporting multi-point fan design with dimension reduction“. Aeronautical Journal 124, Nr. 1279 (27.07.2020): 1371–98. http://dx.doi.org/10.1017/aer.2020.50.
Der volle Inhalt der QuelleNagi, Sajid, Dhruba Kumar Bhattacharyya und Jugal K. Kalita. „A Preview on Subspace Clustering of High Dimensional Data“. INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 6, Nr. 3 (21.05.2013): 441–48. http://dx.doi.org/10.24297/ijct.v6i3.4466.
Der volle Inhalt der QuelleZhou, Jie, Chucheng Huang, Can Gao, Yangbo Wang, Xinrui Shen und Xu Wu. „Weighted Subspace Fuzzy Clustering with Adaptive Projection“. International Journal of Intelligent Systems 2024 (31.01.2024): 1–18. http://dx.doi.org/10.1155/2024/6696775.
Der volle Inhalt der QuellePang, Guansong, Kai Ming Ting, David Albrecht und Huidong Jin. „ZERO++: Harnessing the Power of Zero Appearances to Detect Anomalies in Large-Scale Data Sets“. Journal of Artificial Intelligence Research 57 (29.12.2016): 593–620. http://dx.doi.org/10.1613/jair.5228.
Der volle Inhalt der QuelleIl’in, V. P. „Projection Methods in Krylov Subspaces“. Journal of Mathematical Sciences 240, Nr. 6 (28.06.2019): 772–82. http://dx.doi.org/10.1007/s10958-019-04395-7.
Der volle Inhalt der QuelleDissertationen zum Thema "Subspaces methods"
Shank, Stephen David. „Low-rank solution methods for large-scale linear matrix equations“. Diss., Temple University Libraries, 2014. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/273331.
Der volle Inhalt der QuellePh.D.
We consider low-rank solution methods for certain classes of large-scale linear matrix equations. Our aim is to adapt existing low-rank solution methods based on standard, extended and rational Krylov subspaces to solve equations which may viewed as extensions of the classical Lyapunov and Sylvester equations. The first class of matrix equations that we consider are constrained Sylvester equations, which essentially consist of Sylvester's equation along with a constraint on the solution matrix. These therefore constitute a system of matrix equations. The second are generalized Lyapunov equations, which are Lyapunov equations with additional terms. Such equations arise as computational bottlenecks in model order reduction.
Temple University--Theses
UGWU, UGOCHUKWU OBINNA. „Iterative tensor factorization based on Krylov subspace-type methods with applications to image processing“. Kent State University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=kent1633531487559183.
Der volle Inhalt der QuelleHossain, Mohammad Sahadet. „Numerical Methods for Model Reduction of Time-Varying Descriptor Systems“. Doctoral thesis, Universitätsbibliothek Chemnitz, 2011. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-74776.
Der volle Inhalt der QuelleAhmed, Nisar. „Implicit restart schemes for Krylov subspace model reduction methods“. Thesis, Imperial College London, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.340535.
Der volle Inhalt der QuelleShatnawi, Heba Awad Addad. „Frequency estimation using subspace methods“. Thesis, Wichita State University, 2009. http://hdl.handle.net/10057/2419.
Der volle Inhalt der QuelleThesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical and Computer Engineering
Ensor, Jonathan Edward. „Subspace methods for eigenstructure assignment“. Thesis, University of York, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.341821.
Der volle Inhalt der QuelleMestrah, Ali. „Identification de modèles sous forme de représentation d'état pour les systèmes à sortie binaire“. Electronic Thesis or Diss., Normandie, 2023. http://www.theses.fr/2023NORMC255.
Der volle Inhalt der QuelleThis thesis focuses on parametric modeling of invariant linear systems from binary output measurements. This identification problem is addressed via the use ofsubspace methods. These methods allow the estimation of state-space models, an added benefit of these methods being the fact that their implementation doesnot require the prior knowledge of the order of the system. These methods are initially adapted to high resolution data processing, the objective of this thesis istherefore their adaptation to the identification using binary measurements. In this thesis we propose three subspace methods. Convergence properties of two ofthem are established. Monte Carlo simulation results are presented to show the good performance, but also limits, of these methods
Nguyen, Hieu. „Linear subspace methods in face recognition“. Thesis, University of Nottingham, 2011. http://eprints.nottingham.ac.uk/12330/.
Der volle Inhalt der QuelleTao, Dacheng. „Discriminative linear and multilinear subspace methods“. Thesis, Birkbeck (University of London), 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.438996.
Der volle Inhalt der QuelleYu, Xuebo. „Generalized Krylov subspace methods with applications“. Kent State University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=kent1401937618.
Der volle Inhalt der QuelleBücher zum Thema "Subspaces methods"
Demmel, James Weldon. Three methods for refining estimates of invariant subspaces. New York: Courant Institute of Mathematical Sciences, New York University, 1985.
Den vollen Inhalt der Quelle findenWatkins, David S. The matrix eigenvalue problem: GR and Krylov subspace methods. Philadelphia: Society for Industrial and Applied Mathematics, 2007.
Den vollen Inhalt der Quelle findenMats, Viberg, und Stoica Petre 1949-, Hrsg. Subspace methods. Amsterdam: Elsevier, 1996.
Den vollen Inhalt der Quelle findenKatayama, Tohru. Subspace methods for system identification. London: Springer, 2005.
Den vollen Inhalt der Quelle findenKatayama, Tohru. Subspace Methods for System Identification. London: Springer London, 2005. http://dx.doi.org/10.1007/1-84628-158-x.
Der volle Inhalt der QuelleSaad, Y. Krylov subspace methods on supercomputers. [Moffett Field, Calif.?]: Research Institute for Advanced Computer Science, NASA Ames Research Center, 1988.
Den vollen Inhalt der Quelle findenSogabe, Tomohiro. Krylov Subspace Methods for Linear Systems. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-8532-4.
Der volle Inhalt der QuelleHeeger, David J. Subspace methods for recovering rigid motion. Toronto, Ont: University of Toronto, 1990.
Den vollen Inhalt der Quelle findenJepson, Allan D. Linear subspace methods for recovering translational direction. Toronto: University of Toronto, Dept. of Computer Science, 1992.
Den vollen Inhalt der Quelle findenF, Chan Tony, und Research Institute for Advanced Computer Science (U.S.), Hrsg. Preserving symmetry in preconditioned Krylov subspace methods. [Moffett Field, Calif.]: Research Institute for Advanced Computer Science, NASA Ames Research Center, 1996.
Den vollen Inhalt der Quelle findenBuchteile zum Thema "Subspaces methods"
Schechter, Martin. „Estimates on Subspaces“. In Linking Methods in Critical Point Theory, 131–44. Boston, MA: Birkhäuser Boston, 1999. http://dx.doi.org/10.1007/978-1-4612-1596-7_6.
Der volle Inhalt der QuelleDowney, R. G., und Jeffrey B. Remmel. „Effectively and Noneffectively Nowhere Simple Subspaces“. In Logical Methods, 314–51. Boston, MA: Birkhäuser Boston, 1993. http://dx.doi.org/10.1007/978-1-4612-0325-4_10.
Der volle Inhalt der QuelleNenciu, G. „Almost Invariant Subspaces for Quantum Evolutions“. In Multiscale Methods in Quantum Mechanics, 83–97. Boston, MA: Birkhäuser Boston, 2004. http://dx.doi.org/10.1007/978-0-8176-8202-6_7.
Der volle Inhalt der QuelleFischer, Bernd. „Orthogonal Polynomials and Krylov Subspaces“. In Polynomial Based Iteration Methods for Symmetric Linear Systems, 132–36. Wiesbaden: Vieweg+Teubner Verlag, 1996. http://dx.doi.org/10.1007/978-3-663-11108-5_4.
Der volle Inhalt der QuelleFroelich, John, und Michael Marsalli. „Operator Semigroups, Invariant Sets and Invariant Subspaces“. In Algebraic Methods in Operator Theory, 10–14. Boston, MA: Birkhäuser Boston, 1994. http://dx.doi.org/10.1007/978-1-4612-0255-4_2.
Der volle Inhalt der QuelleIlin, Valery P. „Multi-preconditioned Domain Decomposition Methods in the Krylov Subspaces“. In Lecture Notes in Computer Science, 95–106. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-57099-0_9.
Der volle Inhalt der QuelleAnton, Cristina, und Iain Smith. „Model Based Clustering of Functional Data with Mild Outliers“. In Studies in Classification, Data Analysis, and Knowledge Organization, 11–19. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-09034-9_2.
Der volle Inhalt der QuelleBoot, Tom, und Didier Nibbering. „Subspace Methods“. In Macroeconomic Forecasting in the Era of Big Data, 267–91. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31150-6_9.
Der volle Inhalt der QuelleFukui, Kazuhiro. „Subspace Methods“. In Computer Vision, 1–5. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-03243-2_708-1.
Der volle Inhalt der QuelleFukui, Kazuhiro. „Subspace Methods“. In Computer Vision, 777–81. Boston, MA: Springer US, 2014. http://dx.doi.org/10.1007/978-0-387-31439-6_708.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Subspaces methods"
Zhou, Lei, Xiao Bai, Dong Wang, Xianglong Liu, Jun Zhou und Edwin Hancock. „Latent Distribution Preserving Deep Subspace Clustering“. In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/617.
Der volle Inhalt der QuelleRenaud, J. E., und G. A. Gabriele. „Sequential Global Approximation in Non-Hierarchic System Decomposition and Optimization“. In ASME 1991 Design Technical Conferences. American Society of Mechanical Engineers, 1991. http://dx.doi.org/10.1115/detc1991-0086.
Der volle Inhalt der QuelleYing, Shihui, Lipeng Cai, Changzhou He und Yaxin Peng. „Geometric Understanding for Unsupervised Subspace Learning“. In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/579.
Der volle Inhalt der QuelleTripathy, Rohit, und Ilias Bilionis. „Deep Active Subspaces: A Scalable Method for High-Dimensional Uncertainty Propagation“. In ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/detc2019-98099.
Der volle Inhalt der QuelleArora, Akhil, Alberto Garcia-Duran und Robert West. „Low-Rank Subspaces for Unsupervised Entity Linking“. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics, 2021. http://dx.doi.org/10.18653/v1/2021.emnlp-main.634.
Der volle Inhalt der QuelleXie, Zhihui, Handong Zhao, Tong Yu und Shuai Li. „Discovering Low-rank Subspaces for Language-agnostic Multilingual Representations“. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics, 2022. http://dx.doi.org/10.18653/v1/2022.emnlp-main.379.
Der volle Inhalt der QuelleSmith, Malcolm J., T. S. Koko und I. R. Orisamolu. „Comparative Assessment of Optimal Control Methods With Integrated Performance Constraints“. In ASME 1998 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1998. http://dx.doi.org/10.1115/imece1998-0947.
Der volle Inhalt der QuelleBahamonde, Juan S., Matteo Pini und Piero Colonna. „ACTIVE SUBSPACES FOR THE PRELIMINARY FLUID DYNAMIC DESIGN OF UNCONVENTIONAL TURBOMACHINERY“. In VII European Congress on Computational Methods in Applied Sciences and Engineering. Athens: Institute of Structural Analysis and Antiseismic Research School of Civil Engineering National Technical University of Athens (NTUA) Greece, 2016. http://dx.doi.org/10.7712/100016.2433.7806.
Der volle Inhalt der QuelleAl-Seraji, Najm Abdulzahra Makhrib, Abeer Jabbar Al-Rikabi und Emad Bakr Al-Zangana. „Represent the space PG(3, 8) by subspaces and sub-geometries“. In INTERNATIONAL CONFERENCE OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING ICCMSE 2021. AIP Publishing, 2023. http://dx.doi.org/10.1063/5.0114859.
Der volle Inhalt der QuelleChapron, Maxime, Christophe Blondeau, Michel Bergmann, Itham Salah el Din und Denis Sipp. „SCALABLE CLUSTERED ACTIVE SUBSPACES FOR KRIGING REGRESSION IN HIGH DIMENSION“. In 15th International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control. Athens: Institute of Structural Analysis and Antiseismic Research National Technical University of Athens, 2023. http://dx.doi.org/10.7712/140123.10192.18902.
Der volle Inhalt der QuelleBerichte der Organisationen zum Thema "Subspaces methods"
Harris, D. B. Characterizing source regions with signal subspace methods: Theory and computational methods. Office of Scientific and Technical Information (OSTI), Dezember 1989. http://dx.doi.org/10.2172/5041042.
Der volle Inhalt der QuelleWang, Qiqi. Active Subspace Methods for Data-Intensive Inverse Problems. Office of Scientific and Technical Information (OSTI), April 2017. http://dx.doi.org/10.2172/1353429.
Der volle Inhalt der QuelleConstantine, Paul. Active Subspace Methods for Data-Intensive Inverse Problems. Office of Scientific and Technical Information (OSTI), September 2019. http://dx.doi.org/10.2172/1566065.
Der volle Inhalt der QuelleCarson, Erin, Nicholas Knight und James Demmel. Avoiding Communication in Two-Sided Krylov Subspace Methods. Fort Belvoir, VA: Defense Technical Information Center, August 2011. http://dx.doi.org/10.21236/ada555879.
Der volle Inhalt der QuelleMeza, Juan C., und W. W. Symes. Deflated Krylov Subspace Methods for Nearly Singular Linear Systems. Fort Belvoir, VA: Defense Technical Information Center, Februar 1987. http://dx.doi.org/10.21236/ada455101.
Der volle Inhalt der QuelleNeedell, Deanna, und Rachel Ward. Two-subspace Projection Method for Coherent Overdetermined Systems. Claremont Colleges Digital Library, 2012. http://dx.doi.org/10.5642/tspmcos.2012.01.
Der volle Inhalt der QuelleBui-Thanh, Tan. Active Subspace Methods for Data-Intensive Inverse Problems (Final Report). Office of Scientific and Technical Information (OSTI), Februar 2019. http://dx.doi.org/10.2172/1494035.
Der volle Inhalt der QuelleLi, Zhilin, und Kazufumi Ito. Subspace Iteration and Immersed Interface Methods: Theory, Algorithm, and Applications. Fort Belvoir, VA: Defense Technical Information Center, August 2010. http://dx.doi.org/10.21236/ada532686.
Der volle Inhalt der QuelleElman, Howard C. Multigrid and Krylov Subspace Methods for the Discrete Stokes Equations. Fort Belvoir, VA: Defense Technical Information Center, Juni 1994. http://dx.doi.org/10.21236/ada598913.
Der volle Inhalt der QuelleFreund, R. W., und N. M. Nachtigal. A new Krylov-subspace method for symmetric indefinite linear systems. Office of Scientific and Technical Information (OSTI), Oktober 1994. http://dx.doi.org/10.2172/10190810.
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